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      Species-wide genome sequence and nucleotide polymorphisms from the model allopolyploid plant Brassica napus

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          Abstract

          Brassica napus (oilseed rape, canola) is one of the world’s most important sources of vegetable oil for human nutrition and biofuel, and also a model species for studies investigating the evolutionary consequences of polyploidisation. Strong bottlenecks during its recent origin from interspecific hybridisation, and subsequently through intensive artificial selection, have severely depleted the genetic diversity available for breeding. On the other hand, high-throughput genome profiling technologies today provide unprecedented scope to identify, characterise and utilise genetic diversity in primary and secondary crop gene pools. Such methods also enable implementation of genomic selection strategies to accelerate breeding progress. The key prerequisite is availability of high-quality sequence data and identification of high-quality, genome-wide sequence polymorphisms representing relevant gene pools. We present comprehensive genome resequencing data from a panel of 52 highly diverse natural and synthetic B. napus accessions, along with a stringently selected panel of 4.3 million high-confidence, genome-wide SNPs. The data is of great interest for genomics-assisted breeding and for evolutionary studies on the origins and consequences in allopolyploidisation in plants.

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          Most cited references12

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          A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.

          Heng Li (2011)
          Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. http://samtools.sourceforge.net. hengli@broadinstitute.org.
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            Associative transcriptomics of traits in the polyploid crop species Brassica napus.

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              Patterns of molecular variation in a species-wide germplasm set of Brassica napus.

              Rapeseed (Brassica napus L.) is the leading European oilseed crop serving as source for edible oil and renewable energy. The objectives of our study were to (i) examine the population structure of a large and diverse set of B. napus inbred lines, (ii) investigate patterns of genetic diversity within and among different germplasm types, (iii) compare the two genomes of B. napus with regard to genetic diversity, and (iv) assess the extent of linkage disequilibrium (LD) between simple sequence repeat (SSR) markers. Our study was based on 509 B. napus inbred lines genotyped with 89 genome-specific SSR primer combinations. Both a principal coordinate analysis and software STRUCTURE revealed that winter types, spring types, and swedes were assigned to three major clusters. The genetic diversity of winter oilseed rape was lower than the diversity found in other germplasm types. Within winter oilseed rape types, a decay of genetic diversity with more recent release dates and reduced levels of erucic acid and glucosinolates was observed. The percentage of linked SSR loci pairs in significant (r (2) > Q (95 unlinked loci pairs)) LD was 6.29% for the entire germplasm set. Furthermore, LD decayed rapidly with distance, which will allow a relatively high mapping resolution in genome-wide association studies using our germplasm set, but, on the other hand, will require a high number of markers.
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                Author and article information

                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group
                2052-4463
                08 December 2015
                2015
                : 2
                : 150072
                Affiliations
                [1 ]Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben , Corrensstraße 3, Stadt Seeland 06466, Germany
                [2 ]Justus Liebig University, Department of Plant Breeding , Heinrich-Buff-Ring 26-32, Gießen 35392, Germany
                [3 ]Syngenta France SAS , 12 chemin de l’Hobit, Saint-Sauveur 31790, France
                [4 ]Deutsche Saatveredelung AG , Weissenburger Straße 5, Lippstadt 59557, Germany
                [5 ]Limagrain GmbH , Salder Str. 4, Peine 31226, Germany
                [6 ]Bayer Crop Science AG , Streichmühler Str. 8, Grundhof 24977, Germany
                [7 ]KWS Saat AG , Grimsehlstr. 31, Einbeck 37555, Germany
                [8 ]NPZ Innovation GmbH, Hohenlieth-Hof , Holtsee 24363, Germany
                [9 ]German Seed Alliance GmbH , Neue Schönholzer Str. 12, Berlin 13187, Germany
                Author notes
                []

                T.S. and B.S. performed bioinformatics analysis and wrote the manuscript. R.S. and U.S. wrote the manuscript. D.S., C.U., S.W. and C.C. were involved in data handling and assisted data analyses. E.D. and D.L. prepared libraries and performed sequencing. S.A., F.B., P.D., Z.M., A.A. and G.L. provided data material and contributed in data assessment. All authors read and improved the manuscript.

                [*]

                These authors contributed equally to this work.

                Author information
                http://orcid.org/0000-0003-1073-6719
                http://orcid.org/0000-0001-6113-3518
                Article
                sdata201572
                10.1038/sdata.2015.72
                4672681
                26647166
                886b6277-0f7e-4004-a996-49393cb5abc3
                Copyright © 2015, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse.

                History
                : 21 September 2015
                : 02 November 2015
                Categories
                Data Descriptor

                next-generation sequencing,dna sequencing,plant genetics,agricultural genetics,plant breeding

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